Associate Professor
School of Computer Science and Technology
Harbin Institute of Technology, Shenzhen
Email: sxliu [at] hit [dot] edu [dot] cn
I am an associate professor at the School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen (official homepage in Chinese). Prior to this, I worked as a postdoc (hosted by Xiaohui Bei) at Nanyang Technological University and completed my PhD (advised by Minming Li) at The City University of Hong Kong.
My research focuses on computational economics (EconCS) and theoretical computer science (TCS). My recent interests also include cohesive subgraph mining, with an emphasis on algorithms that combine provable theoretical guarantees with practical efficiency. See DBLP for my full publication list.
Recently, I am interested in the fair division problem in which a set of resources is assigned to a set of agents in a fair manner. In particular, I aim at the generalizations of the classic fair division problem that capture real-world scenarios.
The resources to be allocated contain both divisible and indivisible goods.
Joint work with Xiaohui Bei, Zihao Li, Jinyan Liu, and Xinhang Lu
Fair Division of Mixed Divisible and Indivisible Goods
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2020
Journal version: Artificial Intelligence (AIJ), 293:103436, 2021
AAAI-20 Outstanding Student Paper Award
[arXiv][AAAI][AIJ]
Joint work with Xiaolin Bu, Zihao Li, Xinhang Lu, and Biaoshuai Tao
Best-of-Both-Worlds Fair Allocation of Indivisible and Mixed Goods
In Proceedings of the Conference on Web and Internet Economics (WINE), 2024
[arXiv][WINE]
Joint work with Bo Li, Zihao Li, and Zekai Wu
Allocating Mixed Goods with Customized Fairness and Indivisibility Ratio
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2024
[arXiv][IJCAI]
Joint work with Zihao Li, Xinhang Lu, Biaoshuai Tao, and Yichen Tao
A Complete Landscape for the Price of Envy-Freeness
In Proceedings of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2024
[arXiv][AAMAS]
Joint work with Xinhang Lu, Mashbat Suzuki, and Toby Walsh
Mixed Fair Division: A Survey
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Senior Member Track,
2024
Journal version: Journal of Artificial Intelligence Research (JAIR), 80:1373-1406, 2024
[arXiv][AAAI][JAIR]
Joint work with Zihao Li, Xinhang Lu, and Biaoshuai Tao
Truthful Fair Mechanisms for Allocating Mixed Divisible and Indivisible Goods
In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2023
[arXiv][IJCAI]
Joint work with Xiaohui Bei, Xinhang Lu, and Hongao Wang
Maximin Fairness with Mixed Divisible and Indivisible Goods
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021
Journal version: Autonomous Agents and Multi-Agent Systems (JAAMAS), 35(2): 34, 2021
[arXiv][AAAI][JAAMAS]
Besides the agents, the allocator has the inclination to obtain a fair or efficient allocation based on her own preference.
Joint work with Xiaolin Bu, Zihao Li, Jiaxin Song, and Biaoshuai Tao
Fair Division with Allocator’s Preference
In Proceedings of the Conference on Web and Internet Economics (WINE), 2023
[arXiv][WINE]
Agents have subjective divisibility towards the set of resources.
Joint work with Xiaohui Bei and Xinhang Lu
Fair Division with Subjective Divisibility
In Proceedings of the Conference on Web and Internet Economics (WINE), 2023
Journal version: Games and Economic Behavior (GEB), 151:127-147, 2025
[arXiv][WINE][GEB]
Instead of directly disclosing agents' valuations, the agent responds to the comparison-based query by indicating which of the two bundles she prefers.
Joint work with Zehan Lin, Biaoshuai Tao, and Shengwei Zhou
Comparison-Based Fair Division of Indivisible Chores
In Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA), 2027
[arXiv]
Joint work with Xiaolin Bu, Zihao Li, Jiaxin Song, and Biaoshuai Tao
Logarithmic Comparison-Based Query Complexity for Fair Division of Indivisible Goods
In Proceedings of the Conference on Web and Internet Economics (WINE), 2024
[arXiv][WINE]
Joint work with Zhengyang Liu, Biaoshuai Tao, and Yixin Tao
俱乐部物品公平分配的模型与算法
CCF全国理论计算机科学学术年会, 2026
Joint work with Xiaolin Bu, Zihao Li, Jiaxin Song, and Biaoshuai Tao
Fair Division with Prioritized Agents
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2023
Journal version (also with Ziqi Yu): Information and Computation (IANDC), 2026
[arXiv][AAAI][IANDC]
Joint work with Xiaolin Bu, Zihao Li, Jiaxin Song, and Biaoshuai Tao
Approximability Landscape of Welfare Maximization within Fair Allocations
In Proceedings of the ACM Conference on Economics and Computation (EC), 2025
[arXiv][EC]
I also study efficient algorithms for finding maximum cohesive subgraphs under various relaxations of the clique model.
Yang Liu, Hejiao Huang, Kaiqiang Yu, Shengxin Liu, and Zhaoquan Gu
Efficient Querying of Maximum Connectivity-Based Quasi-Cliques in Large Graphs
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2027
Kewu Yang, Kaiqiang Yu, Shengxin Liu, and Zhaoquan Gu
Revisiting the Maximum Defective Clique Problem: Faster Branching and a Tighter Upper Bound
In Proceedings of the VLDB Endowment (PVLDB), 2026
[arXiv][PVLDB]
Hongbo Xia, Shengxin Liu, and Zhaoquan Gu
Maximum Edge-based Quasi-Clique: Novel Iterative Frameworks
In Proceedings of the ACM Web Conference (WWW), 2026
[arXiv][WWW]
Hongbo Xia, Kaiqiang Yu, Shengxin Liu, Cheng Long, and Xun Zhou
Maximum Degree-Based Quasi-Clique Search via an Iterative Framework
In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
[arXiv][KDD]
Yang Liu, Hejiao Huang, Kaiqiang Yu, Shengxin Liu, and Cheng Long
Efficient Maximum s-Bundle Search via Local Vertex Connectivity
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2025
[SIGMOD]
Shuohao Gao, Kaiqiang Yu, Shengxin Liu, and Cheng Long
Maximum k-Plex Search: An Alternated Reduction-and-Bound Method
In Proceedings of the VLDB Endowment (PVLDB), 2025
[arXiv][PVLDB]
Yinyu Liu, Kaiqiang Yu, Shengxin Liu, Cheng Long, and Xun Zhou
Querying Cohesive Subgraphs in Temporal Graphs
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2026
[SIGMOD]
Yang Liu, Hejiao Huang, Kaiqiang Yu, Shengxin Liu, Cheng Long, and Zhaoquan Gu
Efficient Size-Bounded Community Search, Revisited: Frameworks for Practical Improvements
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2026
[SIGMOD]
Kaiqiang Yu, Cheng Long, Shengxin Liu, and Da Yan
Efficient Algorithms for Maximal k-Biplex Enumeration
In Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2022
[arXiv][SIGMOD]